Merge remote-tracking branch 'origin/main' into pr-1546
This commit is contained in:
1
.gitignore
vendored
1
.gitignore
vendored
@@ -1,3 +1,4 @@
|
||||
.worktrees/
|
||||
.assets
|
||||
.env
|
||||
*.pyc
|
||||
|
||||
42
README.md
42
README.md
@@ -12,11 +12,11 @@
|
||||
</p>
|
||||
</div>
|
||||
|
||||
🐈 **nanobot** is an **ultra-lightweight** personal AI assistant inspired by [OpenClaw](https://github.com/openclaw/openclaw)
|
||||
🐈 **nanobot** is an **ultra-lightweight** personal AI assistant inspired by [OpenClaw](https://github.com/openclaw/openclaw).
|
||||
|
||||
⚡️ Delivers core agent functionality in just **~4,000** lines of code — **99% smaller** than Clawdbot's 430k+ lines.
|
||||
⚡️ Delivers core agent functionality with **99% fewer lines of code** than OpenClaw.
|
||||
|
||||
📏 Real-time line count: **3,935 lines** (run `bash core_agent_lines.sh` to verify anytime)
|
||||
📏 Real-time line count: run `bash core_agent_lines.sh` to verify anytime.
|
||||
|
||||
## 📢 News
|
||||
|
||||
@@ -293,12 +293,18 @@ If you prefer to configure manually, add the following to `~/.nanobot/config.jso
|
||||
"discord": {
|
||||
"enabled": true,
|
||||
"token": "YOUR_BOT_TOKEN",
|
||||
"allowFrom": ["YOUR_USER_ID"]
|
||||
"allowFrom": ["YOUR_USER_ID"],
|
||||
"groupPolicy": "mention"
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
> `groupPolicy` controls how the bot responds in group channels:
|
||||
> - `"mention"` (default) — Only respond when @mentioned
|
||||
> - `"open"` — Respond to all messages
|
||||
> DMs always respond when the sender is in `allowFrom`.
|
||||
|
||||
**5. Invite the bot**
|
||||
- OAuth2 → URL Generator
|
||||
- Scopes: `bot`
|
||||
@@ -658,6 +664,7 @@ Config file: `~/.nanobot/config.json`
|
||||
> - **Zhipu Coding Plan**: If you're on Zhipu's coding plan, set `"apiBase": "https://open.bigmodel.cn/api/coding/paas/v4"` in your zhipu provider config.
|
||||
> - **MiniMax (Mainland China)**: If your API key is from MiniMax's mainland China platform (minimaxi.com), set `"apiBase": "https://api.minimaxi.com/v1"` in your minimax provider config.
|
||||
> - **VolcEngine Coding Plan**: If you're on VolcEngine's coding plan, set `"apiBase": "https://ark.cn-beijing.volces.com/api/coding/v3"` in your volcengine provider config.
|
||||
> - **Alibaba Cloud Coding Plan**: If you're on the Alibaba Cloud Coding Plan (BaiLian), set `"apiBase": "https://coding.dashscope.aliyuncs.com/v1"` in your dashscope provider config.
|
||||
|
||||
| Provider | Purpose | Get API Key |
|
||||
|----------|---------|-------------|
|
||||
@@ -884,6 +891,33 @@ MCP tools are automatically discovered and registered on startup. The LLM can us
|
||||
| `channels.*.allowFrom` | `[]` (allow all) | Whitelist of user IDs. Empty = allow everyone; non-empty = only listed users can interact. |
|
||||
|
||||
|
||||
## Multiple Instances
|
||||
|
||||
Run multiple nanobot instances simultaneously, each with its own workspace and configuration.
|
||||
|
||||
```bash
|
||||
# Instance A - Telegram bot
|
||||
nanobot gateway -w ~/.nanobot/botA -p 18791
|
||||
|
||||
# Instance B - Discord bot
|
||||
nanobot gateway -w ~/.nanobot/botB -p 18792
|
||||
|
||||
# Instance C - Using custom config file
|
||||
nanobot gateway -w ~/.nanobot/botC -c ~/.nanobot/botC/config.json -p 18793
|
||||
```
|
||||
|
||||
| Option | Short | Description |
|
||||
|--------|-------|-------------|
|
||||
| `--workspace` | `-w` | Workspace directory (default: `~/.nanobot/workspace`) |
|
||||
| `--config` | `-c` | Config file path (default: `~/.nanobot/config.json`) |
|
||||
| `--port` | `-p` | Gateway port (default: `18790`) |
|
||||
|
||||
Each instance has its own:
|
||||
- Workspace directory (MEMORY.md, HEARTBEAT.md, session files)
|
||||
- Cron jobs storage (`workspace/cron/jobs.json`)
|
||||
- Configuration (if using `--config`)
|
||||
|
||||
|
||||
## CLI Reference
|
||||
|
||||
| Command | Description |
|
||||
|
||||
@@ -10,6 +10,7 @@ from typing import Any
|
||||
|
||||
from nanobot.agent.memory import MemoryStore
|
||||
from nanobot.agent.skills import SkillsLoader
|
||||
from nanobot.utils.helpers import detect_image_mime
|
||||
|
||||
|
||||
class ContextBuilder:
|
||||
@@ -136,10 +137,14 @@ Reply directly with text for conversations. Only use the 'message' tool to send
|
||||
images = []
|
||||
for path in media:
|
||||
p = Path(path)
|
||||
mime, _ = mimetypes.guess_type(path)
|
||||
if not p.is_file() or not mime or not mime.startswith("image/"):
|
||||
if not p.is_file():
|
||||
continue
|
||||
b64 = base64.b64encode(p.read_bytes()).decode()
|
||||
raw = p.read_bytes()
|
||||
# Detect real MIME type from magic bytes; fallback to filename guess
|
||||
mime = detect_image_mime(raw) or mimetypes.guess_type(path)[0]
|
||||
if not mime or not mime.startswith("image/"):
|
||||
continue
|
||||
b64 = base64.b64encode(raw).decode()
|
||||
images.append({"type": "image_url", "image_url": {"url": f"data:{mime};base64,{b64}"}})
|
||||
|
||||
if not images:
|
||||
|
||||
@@ -202,9 +202,18 @@ class AgentLoop:
|
||||
|
||||
if response.has_tool_calls:
|
||||
if on_progress:
|
||||
clean = self._strip_think(response.content)
|
||||
if clean:
|
||||
await on_progress(clean)
|
||||
thoughts = [
|
||||
self._strip_think(response.content),
|
||||
response.reasoning_content,
|
||||
*(
|
||||
f"Thinking [{b.get('signature', '...')}]:\n{b.get('thought', '...')}"
|
||||
for b in (response.thinking_blocks or [])
|
||||
if isinstance(b, dict) and "signature" in b
|
||||
),
|
||||
]
|
||||
combined_thoughts = "\n\n".join(filter(None, thoughts))
|
||||
if combined_thoughts:
|
||||
await on_progress(combined_thoughts)
|
||||
await on_progress(self._tool_hint(response.tool_calls), tool_hint=True)
|
||||
|
||||
tool_call_dicts = [
|
||||
|
||||
@@ -128,6 +128,13 @@ class MemoryStore:
|
||||
# Some providers return arguments as a JSON string instead of dict
|
||||
if isinstance(args, str):
|
||||
args = json.loads(args)
|
||||
# Some providers return arguments as a list (handle edge case)
|
||||
if isinstance(args, list):
|
||||
if args and isinstance(args[0], dict):
|
||||
args = args[0]
|
||||
else:
|
||||
logger.warning("Memory consolidation: unexpected arguments as empty or non-dict list")
|
||||
return False
|
||||
if not isinstance(args, dict):
|
||||
logger.warning("Memory consolidation: unexpected arguments type {}", type(args).__name__)
|
||||
return False
|
||||
|
||||
@@ -58,17 +58,48 @@ async def connect_mcp_servers(
|
||||
) -> None:
|
||||
"""Connect to configured MCP servers and register their tools."""
|
||||
from mcp import ClientSession, StdioServerParameters
|
||||
from mcp.client.sse import sse_client
|
||||
from mcp.client.stdio import stdio_client
|
||||
from mcp.client.streamable_http import streamable_http_client
|
||||
|
||||
for name, cfg in mcp_servers.items():
|
||||
try:
|
||||
if cfg.command:
|
||||
transport_type = cfg.type
|
||||
if not transport_type:
|
||||
if cfg.command:
|
||||
transport_type = "stdio"
|
||||
elif cfg.url:
|
||||
# Convention: URLs ending with /sse use SSE transport; others use streamableHttp
|
||||
transport_type = (
|
||||
"sse" if cfg.url.rstrip("/").endswith("/sse") else "streamableHttp"
|
||||
)
|
||||
else:
|
||||
logger.warning("MCP server '{}': no command or url configured, skipping", name)
|
||||
continue
|
||||
|
||||
if transport_type == "stdio":
|
||||
params = StdioServerParameters(
|
||||
command=cfg.command, args=cfg.args, env=cfg.env or None
|
||||
)
|
||||
read, write = await stack.enter_async_context(stdio_client(params))
|
||||
elif cfg.url:
|
||||
from mcp.client.streamable_http import streamable_http_client
|
||||
elif transport_type == "sse":
|
||||
def httpx_client_factory(
|
||||
headers: dict[str, str] | None = None,
|
||||
timeout: httpx.Timeout | None = None,
|
||||
auth: httpx.Auth | None = None,
|
||||
) -> httpx.AsyncClient:
|
||||
merged_headers = {**(cfg.headers or {}), **(headers or {})}
|
||||
return httpx.AsyncClient(
|
||||
headers=merged_headers or None,
|
||||
follow_redirects=True,
|
||||
timeout=timeout,
|
||||
auth=auth,
|
||||
)
|
||||
|
||||
read, write = await stack.enter_async_context(
|
||||
sse_client(cfg.url, httpx_client_factory=httpx_client_factory)
|
||||
)
|
||||
elif transport_type == "streamableHttp":
|
||||
# Always provide an explicit httpx client so MCP HTTP transport does not
|
||||
# inherit httpx's default 5s timeout and preempt the higher-level tool timeout.
|
||||
http_client = await stack.enter_async_context(
|
||||
@@ -82,7 +113,7 @@ async def connect_mcp_servers(
|
||||
streamable_http_client(cfg.url, http_client=http_client)
|
||||
)
|
||||
else:
|
||||
logger.warning("MCP server '{}': no command or url configured, skipping", name)
|
||||
logger.warning("MCP server '{}': unknown transport type '{}'", name, transport_type)
|
||||
continue
|
||||
|
||||
session = await stack.enter_async_context(ClientSession(read, write))
|
||||
|
||||
@@ -13,34 +13,13 @@ from nanobot.bus.events import OutboundMessage
|
||||
from nanobot.bus.queue import MessageBus
|
||||
from nanobot.channels.base import BaseChannel
|
||||
from nanobot.config.schema import DiscordConfig
|
||||
from nanobot.utils.helpers import split_message
|
||||
|
||||
DISCORD_API_BASE = "https://discord.com/api/v10"
|
||||
MAX_ATTACHMENT_BYTES = 20 * 1024 * 1024 # 20MB
|
||||
MAX_MESSAGE_LEN = 2000 # Discord message character limit
|
||||
|
||||
|
||||
def _split_message(content: str, max_len: int = MAX_MESSAGE_LEN) -> list[str]:
|
||||
"""Split content into chunks within max_len, preferring line breaks."""
|
||||
if not content:
|
||||
return []
|
||||
if len(content) <= max_len:
|
||||
return [content]
|
||||
chunks: list[str] = []
|
||||
while content:
|
||||
if len(content) <= max_len:
|
||||
chunks.append(content)
|
||||
break
|
||||
cut = content[:max_len]
|
||||
pos = cut.rfind('\n')
|
||||
if pos <= 0:
|
||||
pos = cut.rfind(' ')
|
||||
if pos <= 0:
|
||||
pos = max_len
|
||||
chunks.append(content[:pos])
|
||||
content = content[pos:].lstrip()
|
||||
return chunks
|
||||
|
||||
|
||||
class DiscordChannel(BaseChannel):
|
||||
"""Discord channel using Gateway websocket."""
|
||||
|
||||
@@ -54,6 +33,7 @@ class DiscordChannel(BaseChannel):
|
||||
self._heartbeat_task: asyncio.Task | None = None
|
||||
self._typing_tasks: dict[str, asyncio.Task] = {}
|
||||
self._http: httpx.AsyncClient | None = None
|
||||
self._bot_user_id: str | None = None
|
||||
|
||||
async def start(self) -> None:
|
||||
"""Start the Discord gateway connection."""
|
||||
@@ -104,7 +84,7 @@ class DiscordChannel(BaseChannel):
|
||||
headers = {"Authorization": f"Bot {self.config.token}"}
|
||||
|
||||
try:
|
||||
chunks = _split_message(msg.content or "")
|
||||
chunks = split_message(msg.content or "", MAX_MESSAGE_LEN)
|
||||
if not chunks:
|
||||
return
|
||||
|
||||
@@ -170,6 +150,10 @@ class DiscordChannel(BaseChannel):
|
||||
await self._identify()
|
||||
elif op == 0 and event_type == "READY":
|
||||
logger.info("Discord gateway READY")
|
||||
# Capture bot user ID for mention detection
|
||||
user_data = payload.get("user") or {}
|
||||
self._bot_user_id = user_data.get("id")
|
||||
logger.info("Discord bot connected as user {}", self._bot_user_id)
|
||||
elif op == 0 and event_type == "MESSAGE_CREATE":
|
||||
await self._handle_message_create(payload)
|
||||
elif op == 7:
|
||||
@@ -226,6 +210,7 @@ class DiscordChannel(BaseChannel):
|
||||
sender_id = str(author.get("id", ""))
|
||||
channel_id = str(payload.get("channel_id", ""))
|
||||
content = payload.get("content") or ""
|
||||
guild_id = payload.get("guild_id")
|
||||
|
||||
if not sender_id or not channel_id:
|
||||
return
|
||||
@@ -233,6 +218,11 @@ class DiscordChannel(BaseChannel):
|
||||
if not self.is_allowed(sender_id):
|
||||
return
|
||||
|
||||
# Check group channel policy (DMs always respond if is_allowed passes)
|
||||
if guild_id is not None:
|
||||
if not self._should_respond_in_group(payload, content):
|
||||
return
|
||||
|
||||
content_parts = [content] if content else []
|
||||
media_paths: list[str] = []
|
||||
media_dir = Path.home() / ".nanobot" / "media"
|
||||
@@ -269,11 +259,32 @@ class DiscordChannel(BaseChannel):
|
||||
media=media_paths,
|
||||
metadata={
|
||||
"message_id": str(payload.get("id", "")),
|
||||
"guild_id": payload.get("guild_id"),
|
||||
"guild_id": guild_id,
|
||||
"reply_to": reply_to,
|
||||
},
|
||||
)
|
||||
|
||||
def _should_respond_in_group(self, payload: dict[str, Any], content: str) -> bool:
|
||||
"""Check if bot should respond in a group channel based on policy."""
|
||||
if self.config.group_policy == "open":
|
||||
return True
|
||||
|
||||
if self.config.group_policy == "mention":
|
||||
# Check if bot was mentioned in the message
|
||||
if self._bot_user_id:
|
||||
# Check mentions array
|
||||
mentions = payload.get("mentions") or []
|
||||
for mention in mentions:
|
||||
if str(mention.get("id")) == self._bot_user_id:
|
||||
return True
|
||||
# Also check content for mention format <@USER_ID>
|
||||
if f"<@{self._bot_user_id}>" in content or f"<@!{self._bot_user_id}>" in content:
|
||||
return True
|
||||
logger.debug("Discord message in {} ignored (bot not mentioned)", payload.get("channel_id"))
|
||||
return False
|
||||
|
||||
return True
|
||||
|
||||
async def _start_typing(self, channel_id: str) -> None:
|
||||
"""Start periodic typing indicator for a channel."""
|
||||
await self._stop_typing(channel_id)
|
||||
|
||||
@@ -290,16 +290,28 @@ class FeishuChannel(BaseChannel):
|
||||
log_level=lark.LogLevel.INFO
|
||||
)
|
||||
|
||||
# Start WebSocket client in a separate thread with reconnect loop
|
||||
# Start WebSocket client in a separate thread with reconnect loop.
|
||||
# A dedicated event loop is created for this thread so that lark_oapi's
|
||||
# module-level `loop = asyncio.get_event_loop()` picks up an idle loop
|
||||
# instead of the already-running main asyncio loop, which would cause
|
||||
# "This event loop is already running" errors.
|
||||
def run_ws():
|
||||
while self._running:
|
||||
try:
|
||||
self._ws_client.start()
|
||||
except Exception as e:
|
||||
logger.warning("Feishu WebSocket error: {}", e)
|
||||
if self._running:
|
||||
import time
|
||||
time.sleep(5)
|
||||
import time
|
||||
import lark_oapi.ws.client as _lark_ws_client
|
||||
ws_loop = asyncio.new_event_loop()
|
||||
asyncio.set_event_loop(ws_loop)
|
||||
# Patch the module-level loop used by lark's ws Client.start()
|
||||
_lark_ws_client.loop = ws_loop
|
||||
try:
|
||||
while self._running:
|
||||
try:
|
||||
self._ws_client.start()
|
||||
except Exception as e:
|
||||
logger.warning("Feishu WebSocket error: {}", e)
|
||||
if self._running:
|
||||
time.sleep(5)
|
||||
finally:
|
||||
ws_loop.close()
|
||||
|
||||
self._ws_thread = threading.Thread(target=run_ws, daemon=True)
|
||||
self._ws_thread.start()
|
||||
@@ -398,6 +410,34 @@ class FeishuChannel(BaseChannel):
|
||||
elements.extend(self._split_headings(remaining))
|
||||
return elements or [{"tag": "markdown", "content": content}]
|
||||
|
||||
@staticmethod
|
||||
def _split_elements_by_table_limit(elements: list[dict], max_tables: int = 1) -> list[list[dict]]:
|
||||
"""Split card elements into groups with at most *max_tables* table elements each.
|
||||
|
||||
Feishu cards have a hard limit of one table per card (API error 11310).
|
||||
When the rendered content contains multiple markdown tables each table is
|
||||
placed in a separate card message so every table reaches the user.
|
||||
"""
|
||||
if not elements:
|
||||
return [[]]
|
||||
groups: list[list[dict]] = []
|
||||
current: list[dict] = []
|
||||
table_count = 0
|
||||
for el in elements:
|
||||
if el.get("tag") == "table":
|
||||
if table_count >= max_tables:
|
||||
if current:
|
||||
groups.append(current)
|
||||
current = []
|
||||
table_count = 0
|
||||
current.append(el)
|
||||
table_count += 1
|
||||
else:
|
||||
current.append(el)
|
||||
if current:
|
||||
groups.append(current)
|
||||
return groups or [[]]
|
||||
|
||||
def _split_headings(self, content: str) -> list[dict]:
|
||||
"""Split content by headings, converting headings to div elements."""
|
||||
protected = content
|
||||
@@ -432,8 +472,124 @@ class FeishuChannel(BaseChannel):
|
||||
|
||||
return elements or [{"tag": "markdown", "content": content}]
|
||||
|
||||
# ── Smart format detection ──────────────────────────────────────────
|
||||
# Patterns that indicate "complex" markdown needing card rendering
|
||||
_COMPLEX_MD_RE = re.compile(
|
||||
r"```" # fenced code block
|
||||
r"|^\|.+\|.*\n\s*\|[-:\s|]+\|" # markdown table (header + separator)
|
||||
r"|^#{1,6}\s+" # headings
|
||||
, re.MULTILINE,
|
||||
)
|
||||
|
||||
# Simple markdown patterns (bold, italic, strikethrough)
|
||||
_SIMPLE_MD_RE = re.compile(
|
||||
r"\*\*.+?\*\*" # **bold**
|
||||
r"|__.+?__" # __bold__
|
||||
r"|(?<!\*)\*(?!\*)(.+?)(?<!\*)\*(?!\*)" # *italic* (single *)
|
||||
r"|~~.+?~~" # ~~strikethrough~~
|
||||
, re.DOTALL,
|
||||
)
|
||||
|
||||
# Markdown link: [text](url)
|
||||
_MD_LINK_RE = re.compile(r"\[([^\]]+)\]\((https?://[^\)]+)\)")
|
||||
|
||||
# Unordered list items
|
||||
_LIST_RE = re.compile(r"^[\s]*[-*+]\s+", re.MULTILINE)
|
||||
|
||||
# Ordered list items
|
||||
_OLIST_RE = re.compile(r"^[\s]*\d+\.\s+", re.MULTILINE)
|
||||
|
||||
# Max length for plain text format
|
||||
_TEXT_MAX_LEN = 200
|
||||
|
||||
# Max length for post (rich text) format; beyond this, use card
|
||||
_POST_MAX_LEN = 2000
|
||||
|
||||
@classmethod
|
||||
def _detect_msg_format(cls, content: str) -> str:
|
||||
"""Determine the optimal Feishu message format for *content*.
|
||||
|
||||
Returns one of:
|
||||
- ``"text"`` – plain text, short and no markdown
|
||||
- ``"post"`` – rich text (links only, moderate length)
|
||||
- ``"interactive"`` – card with full markdown rendering
|
||||
"""
|
||||
stripped = content.strip()
|
||||
|
||||
# Complex markdown (code blocks, tables, headings) → always card
|
||||
if cls._COMPLEX_MD_RE.search(stripped):
|
||||
return "interactive"
|
||||
|
||||
# Long content → card (better readability with card layout)
|
||||
if len(stripped) > cls._POST_MAX_LEN:
|
||||
return "interactive"
|
||||
|
||||
# Has bold/italic/strikethrough → card (post format can't render these)
|
||||
if cls._SIMPLE_MD_RE.search(stripped):
|
||||
return "interactive"
|
||||
|
||||
# Has list items → card (post format can't render list bullets well)
|
||||
if cls._LIST_RE.search(stripped) or cls._OLIST_RE.search(stripped):
|
||||
return "interactive"
|
||||
|
||||
# Has links → post format (supports <a> tags)
|
||||
if cls._MD_LINK_RE.search(stripped):
|
||||
return "post"
|
||||
|
||||
# Short plain text → text format
|
||||
if len(stripped) <= cls._TEXT_MAX_LEN:
|
||||
return "text"
|
||||
|
||||
# Medium plain text without any formatting → post format
|
||||
return "post"
|
||||
|
||||
@classmethod
|
||||
def _markdown_to_post(cls, content: str) -> str:
|
||||
"""Convert markdown content to Feishu post message JSON.
|
||||
|
||||
Handles links ``[text](url)`` as ``a`` tags; everything else as ``text`` tags.
|
||||
Each line becomes a paragraph (row) in the post body.
|
||||
"""
|
||||
lines = content.strip().split("\n")
|
||||
paragraphs: list[list[dict]] = []
|
||||
|
||||
for line in lines:
|
||||
elements: list[dict] = []
|
||||
last_end = 0
|
||||
|
||||
for m in cls._MD_LINK_RE.finditer(line):
|
||||
# Text before this link
|
||||
before = line[last_end:m.start()]
|
||||
if before:
|
||||
elements.append({"tag": "text", "text": before})
|
||||
elements.append({
|
||||
"tag": "a",
|
||||
"text": m.group(1),
|
||||
"href": m.group(2),
|
||||
})
|
||||
last_end = m.end()
|
||||
|
||||
# Remaining text after last link
|
||||
remaining = line[last_end:]
|
||||
if remaining:
|
||||
elements.append({"tag": "text", "text": remaining})
|
||||
|
||||
# Empty line → empty paragraph for spacing
|
||||
if not elements:
|
||||
elements.append({"tag": "text", "text": ""})
|
||||
|
||||
paragraphs.append(elements)
|
||||
|
||||
post_body = {
|
||||
"zh_cn": {
|
||||
"content": paragraphs,
|
||||
}
|
||||
}
|
||||
return json.dumps(post_body, ensure_ascii=False)
|
||||
|
||||
_IMAGE_EXTS = {".png", ".jpg", ".jpeg", ".gif", ".bmp", ".webp", ".ico", ".tiff", ".tif"}
|
||||
_AUDIO_EXTS = {".opus"}
|
||||
_VIDEO_EXTS = {".mp4", ".mov", ".avi"}
|
||||
_FILE_TYPE_MAP = {
|
||||
".opus": "opus", ".mp4": "mp4", ".pdf": "pdf", ".doc": "doc", ".docx": "doc",
|
||||
".xls": "xls", ".xlsx": "xls", ".ppt": "ppt", ".pptx": "ppt",
|
||||
@@ -642,18 +798,45 @@ class FeishuChannel(BaseChannel):
|
||||
else:
|
||||
key = await loop.run_in_executor(None, self._upload_file_sync, file_path)
|
||||
if key:
|
||||
media_type = "audio" if ext in self._AUDIO_EXTS else "file"
|
||||
# Use msg_type "media" for audio/video so users can play inline;
|
||||
# "file" for everything else (documents, archives, etc.)
|
||||
if ext in self._AUDIO_EXTS or ext in self._VIDEO_EXTS:
|
||||
media_type = "media"
|
||||
else:
|
||||
media_type = "file"
|
||||
await loop.run_in_executor(
|
||||
None, self._send_message_sync,
|
||||
receive_id_type, msg.chat_id, media_type, json.dumps({"file_key": key}, ensure_ascii=False),
|
||||
)
|
||||
|
||||
if msg.content and msg.content.strip():
|
||||
card = {"config": {"wide_screen_mode": True}, "elements": self._build_card_elements(msg.content)}
|
||||
await loop.run_in_executor(
|
||||
None, self._send_message_sync,
|
||||
receive_id_type, msg.chat_id, "interactive", json.dumps(card, ensure_ascii=False),
|
||||
)
|
||||
fmt = self._detect_msg_format(msg.content)
|
||||
|
||||
if fmt == "text":
|
||||
# Short plain text – send as simple text message
|
||||
text_body = json.dumps({"text": msg.content.strip()}, ensure_ascii=False)
|
||||
await loop.run_in_executor(
|
||||
None, self._send_message_sync,
|
||||
receive_id_type, msg.chat_id, "text", text_body,
|
||||
)
|
||||
|
||||
elif fmt == "post":
|
||||
# Medium content with links – send as rich-text post
|
||||
post_body = self._markdown_to_post(msg.content)
|
||||
await loop.run_in_executor(
|
||||
None, self._send_message_sync,
|
||||
receive_id_type, msg.chat_id, "post", post_body,
|
||||
)
|
||||
|
||||
else:
|
||||
# Complex / long content – send as interactive card
|
||||
elements = self._build_card_elements(msg.content)
|
||||
for chunk in self._split_elements_by_table_limit(elements):
|
||||
card = {"config": {"wide_screen_mode": True}, "elements": chunk}
|
||||
await loop.run_in_executor(
|
||||
None, self._send_message_sync,
|
||||
receive_id_type, msg.chat_id, "interactive", json.dumps(card, ensure_ascii=False),
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error("Error sending Feishu message: {}", e)
|
||||
|
||||
@@ -14,6 +14,9 @@ from nanobot.bus.events import OutboundMessage
|
||||
from nanobot.bus.queue import MessageBus
|
||||
from nanobot.channels.base import BaseChannel
|
||||
from nanobot.config.schema import TelegramConfig
|
||||
from nanobot.utils.helpers import split_message
|
||||
|
||||
TELEGRAM_MAX_MESSAGE_LEN = 4000 # Telegram message character limit
|
||||
|
||||
|
||||
def _markdown_to_telegram_html(text: str) -> str:
|
||||
@@ -79,26 +82,6 @@ def _markdown_to_telegram_html(text: str) -> str:
|
||||
return text
|
||||
|
||||
|
||||
def _split_message(content: str, max_len: int = 4000) -> list[str]:
|
||||
"""Split content into chunks within max_len, preferring line breaks."""
|
||||
if len(content) <= max_len:
|
||||
return [content]
|
||||
chunks: list[str] = []
|
||||
while content:
|
||||
if len(content) <= max_len:
|
||||
chunks.append(content)
|
||||
break
|
||||
cut = content[:max_len]
|
||||
pos = cut.rfind('\n')
|
||||
if pos == -1:
|
||||
pos = cut.rfind(' ')
|
||||
if pos == -1:
|
||||
pos = max_len
|
||||
chunks.append(content[:pos])
|
||||
content = content[pos:].lstrip()
|
||||
return chunks
|
||||
|
||||
|
||||
class TelegramChannel(BaseChannel):
|
||||
"""
|
||||
Telegram channel using long polling.
|
||||
@@ -225,7 +208,9 @@ class TelegramChannel(BaseChannel):
|
||||
logger.warning("Telegram bot not running")
|
||||
return
|
||||
|
||||
self._stop_typing(msg.chat_id)
|
||||
# Only stop typing indicator for final responses
|
||||
if not msg.metadata.get("_progress", False):
|
||||
self._stop_typing(msg.chat_id)
|
||||
|
||||
try:
|
||||
chat_id = int(msg.chat_id)
|
||||
@@ -269,23 +254,41 @@ class TelegramChannel(BaseChannel):
|
||||
|
||||
# Send text content
|
||||
if msg.content and msg.content != "[empty message]":
|
||||
for chunk in _split_message(msg.content):
|
||||
is_progress = msg.metadata.get("_progress", False)
|
||||
draft_id = msg.metadata.get("message_id")
|
||||
|
||||
for chunk in split_message(msg.content, TELEGRAM_MAX_MESSAGE_LEN):
|
||||
try:
|
||||
html = _markdown_to_telegram_html(chunk)
|
||||
await self._app.bot.send_message(
|
||||
chat_id=chat_id,
|
||||
text=html,
|
||||
parse_mode="HTML",
|
||||
reply_parameters=reply_params
|
||||
)
|
||||
if is_progress and draft_id:
|
||||
await self._app.bot.send_message_draft(
|
||||
chat_id=chat_id,
|
||||
draft_id=draft_id,
|
||||
text=html,
|
||||
parse_mode="HTML"
|
||||
)
|
||||
else:
|
||||
await self._app.bot.send_message(
|
||||
chat_id=chat_id,
|
||||
text=html,
|
||||
parse_mode="HTML",
|
||||
reply_parameters=reply_params
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning("HTML parse failed, falling back to plain text: {}", e)
|
||||
try:
|
||||
await self._app.bot.send_message(
|
||||
chat_id=chat_id,
|
||||
text=chunk,
|
||||
reply_parameters=reply_params
|
||||
)
|
||||
if is_progress and draft_id:
|
||||
await self._app.bot.send_message_draft(
|
||||
chat_id=chat_id,
|
||||
draft_id=draft_id,
|
||||
text=chunk
|
||||
)
|
||||
else:
|
||||
await self._app.bot.send_message(
|
||||
chat_id=chat_id,
|
||||
text=chunk,
|
||||
reply_parameters=reply_params
|
||||
)
|
||||
except Exception as e2:
|
||||
logger.error("Error sending Telegram message: {}", e2)
|
||||
|
||||
|
||||
@@ -7,6 +7,18 @@ import signal
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
# Force UTF-8 encoding for Windows console
|
||||
if sys.platform == "win32":
|
||||
import locale
|
||||
if sys.stdout.encoding != "utf-8":
|
||||
os.environ["PYTHONIOENCODING"] = "utf-8"
|
||||
# Re-open stdout/stderr with UTF-8 encoding
|
||||
try:
|
||||
sys.stdout.reconfigure(encoding="utf-8", errors="replace")
|
||||
sys.stderr.reconfigure(encoding="utf-8", errors="replace")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
import typer
|
||||
from prompt_toolkit import PromptSession
|
||||
from prompt_toolkit.formatted_text import HTML
|
||||
@@ -244,13 +256,15 @@ def _make_provider(config: Config):
|
||||
@app.command()
|
||||
def gateway(
|
||||
port: int = typer.Option(18790, "--port", "-p", help="Gateway port"),
|
||||
workspace: str | None = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
|
||||
config: str | None = typer.Option(None, "--config", "-c", help="Config file path"),
|
||||
verbose: bool = typer.Option(False, "--verbose", "-v", help="Verbose output"),
|
||||
):
|
||||
"""Start the nanobot gateway."""
|
||||
from nanobot.agent.loop import AgentLoop
|
||||
from nanobot.bus.queue import MessageBus
|
||||
from nanobot.channels.manager import ChannelManager
|
||||
from nanobot.config.loader import get_data_dir, load_config
|
||||
from nanobot.config.loader import load_config
|
||||
from nanobot.cron.service import CronService
|
||||
from nanobot.cron.types import CronJob
|
||||
from nanobot.heartbeat.service import HeartbeatService
|
||||
@@ -260,16 +274,20 @@ def gateway(
|
||||
import logging
|
||||
logging.basicConfig(level=logging.DEBUG)
|
||||
|
||||
console.print(f"{__logo__} Starting nanobot gateway on port {port}...")
|
||||
config_path = Path(config) if config else None
|
||||
config = load_config(config_path)
|
||||
if workspace:
|
||||
config.agents.defaults.workspace = workspace
|
||||
|
||||
config = load_config()
|
||||
console.print(f"{__logo__} Starting nanobot gateway on port {port}...")
|
||||
sync_workspace_templates(config.workspace_path)
|
||||
bus = MessageBus()
|
||||
provider = _make_provider(config)
|
||||
session_manager = SessionManager(config.workspace_path)
|
||||
|
||||
# Create cron service first (callback set after agent creation)
|
||||
cron_store_path = get_data_dir() / "cron" / "jobs.json"
|
||||
# Use workspace path for per-instance cron store
|
||||
cron_store_path = config.workspace_path / "cron" / "jobs.json"
|
||||
cron = CronService(cron_store_path)
|
||||
|
||||
# Create agent with cron service
|
||||
@@ -511,12 +529,21 @@ def agent(
|
||||
else:
|
||||
cli_channel, cli_chat_id = "cli", session_id
|
||||
|
||||
def _exit_on_sigint(signum, frame):
|
||||
def _handle_signal(signum, frame):
|
||||
sig_name = signal.Signals(signum).name
|
||||
_restore_terminal()
|
||||
console.print("\nGoodbye!")
|
||||
os._exit(0)
|
||||
console.print(f"\nReceived {sig_name}, goodbye!")
|
||||
sys.exit(0)
|
||||
|
||||
signal.signal(signal.SIGINT, _exit_on_sigint)
|
||||
signal.signal(signal.SIGINT, _handle_signal)
|
||||
signal.signal(signal.SIGTERM, _handle_signal)
|
||||
# SIGHUP is not available on Windows
|
||||
if hasattr(signal, 'SIGHUP'):
|
||||
signal.signal(signal.SIGHUP, _handle_signal)
|
||||
# Ignore SIGPIPE to prevent silent process termination when writing to closed pipes
|
||||
# SIGPIPE is not available on Windows
|
||||
if hasattr(signal, 'SIGPIPE'):
|
||||
signal.signal(signal.SIGPIPE, signal.SIG_IGN)
|
||||
|
||||
async def run_interactive():
|
||||
bus_task = asyncio.create_task(agent_loop.run())
|
||||
|
||||
@@ -29,7 +29,9 @@ class TelegramConfig(Base):
|
||||
enabled: bool = False
|
||||
token: str = "" # Bot token from @BotFather
|
||||
allow_from: list[str] = Field(default_factory=list) # Allowed user IDs or usernames
|
||||
proxy: str | None = None # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
|
||||
proxy: str | None = (
|
||||
None # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
|
||||
)
|
||||
reply_to_message: bool = False # If true, bot replies quote the original message
|
||||
|
||||
|
||||
@@ -42,7 +44,9 @@ class FeishuConfig(Base):
|
||||
encrypt_key: str = "" # Encrypt Key for event subscription (optional)
|
||||
verification_token: str = "" # Verification Token for event subscription (optional)
|
||||
allow_from: list[str] = Field(default_factory=list) # Allowed user open_ids
|
||||
react_emoji: str = "THUMBSUP" # Emoji type for message reactions (e.g. THUMBSUP, OK, DONE, SMILE)
|
||||
react_emoji: str = (
|
||||
"THUMBSUP" # Emoji type for message reactions (e.g. THUMBSUP, OK, DONE, SMILE)
|
||||
)
|
||||
|
||||
|
||||
class DingTalkConfig(Base):
|
||||
@@ -62,6 +66,7 @@ class DiscordConfig(Base):
|
||||
allow_from: list[str] = Field(default_factory=list) # Allowed user IDs
|
||||
gateway_url: str = "wss://gateway.discord.gg/?v=10&encoding=json"
|
||||
intents: int = 37377 # GUILDS + GUILD_MESSAGES + DIRECT_MESSAGES + MESSAGE_CONTENT
|
||||
group_policy: Literal["mention", "open"] = "mention"
|
||||
|
||||
|
||||
class MatrixConfig(Base):
|
||||
@@ -72,9 +77,13 @@ class MatrixConfig(Base):
|
||||
access_token: str = ""
|
||||
user_id: str = "" # @bot:matrix.org
|
||||
device_id: str = ""
|
||||
e2ee_enabled: bool = True # Enable Matrix E2EE support (encryption + encrypted room handling).
|
||||
sync_stop_grace_seconds: int = 2 # Max seconds to wait for sync_forever to stop gracefully before cancellation fallback.
|
||||
max_media_bytes: int = 20 * 1024 * 1024 # Max attachment size accepted for Matrix media handling (inbound + outbound).
|
||||
e2ee_enabled: bool = True # Enable Matrix E2EE support (encryption + encrypted room handling).
|
||||
sync_stop_grace_seconds: int = (
|
||||
2 # Max seconds to wait for sync_forever to stop gracefully before cancellation fallback.
|
||||
)
|
||||
max_media_bytes: int = (
|
||||
20 * 1024 * 1024
|
||||
) # Max attachment size accepted for Matrix media handling (inbound + outbound).
|
||||
allow_from: list[str] = Field(default_factory=list)
|
||||
group_policy: Literal["open", "mention", "allowlist"] = "open"
|
||||
group_allow_from: list[str] = Field(default_factory=list)
|
||||
@@ -105,7 +114,9 @@ class EmailConfig(Base):
|
||||
from_address: str = ""
|
||||
|
||||
# Behavior
|
||||
auto_reply_enabled: bool = True # If false, inbound email is read but no automatic reply is sent
|
||||
auto_reply_enabled: bool = (
|
||||
True # If false, inbound email is read but no automatic reply is sent
|
||||
)
|
||||
poll_interval_seconds: int = 30
|
||||
mark_seen: bool = True
|
||||
max_body_chars: int = 12000
|
||||
@@ -183,27 +194,17 @@ class QQConfig(Base):
|
||||
enabled: bool = False
|
||||
app_id: str = "" # 机器人 ID (AppID) from q.qq.com
|
||||
secret: str = "" # 机器人密钥 (AppSecret) from q.qq.com
|
||||
allow_from: list[str] = Field(default_factory=list) # Allowed user openids (empty = public access)
|
||||
allow_from: list[str] = Field(
|
||||
default_factory=list
|
||||
) # Allowed user openids (empty = public access)
|
||||
|
||||
|
||||
|
||||
class MatrixConfig(Base):
|
||||
"""Matrix (Element) channel configuration."""
|
||||
enabled: bool = False
|
||||
homeserver: str = "https://matrix.org"
|
||||
access_token: str = ""
|
||||
user_id: str = "" # e.g. @bot:matrix.org
|
||||
device_id: str = ""
|
||||
e2ee_enabled: bool = True # end-to-end encryption support
|
||||
sync_stop_grace_seconds: int = 2 # graceful sync_forever shutdown timeout
|
||||
max_media_bytes: int = 20 * 1024 * 1024 # inbound + outbound attachment limit
|
||||
allow_from: list[str] = Field(default_factory=list)
|
||||
group_policy: Literal["open", "mention", "allowlist"] = "open"
|
||||
group_allow_from: list[str] = Field(default_factory=list)
|
||||
allow_room_mentions: bool = False
|
||||
|
||||
class ChannelsConfig(Base):
|
||||
"""Configuration for chat channels."""
|
||||
|
||||
send_progress: bool = True # stream agent's text progress to the channel
|
||||
send_progress: bool = True # stream agent's text progress to the channel
|
||||
send_tool_hints: bool = False # stream tool-call hints (e.g. read_file("…"))
|
||||
whatsapp: WhatsAppConfig = Field(default_factory=WhatsAppConfig)
|
||||
telegram: TelegramConfig = Field(default_factory=TelegramConfig)
|
||||
@@ -222,7 +223,9 @@ class AgentDefaults(Base):
|
||||
|
||||
workspace: str = "~/.nanobot/workspace"
|
||||
model: str = "anthropic/claude-opus-4-5"
|
||||
provider: str = "auto" # Provider name (e.g. "anthropic", "openrouter") or "auto" for auto-detection
|
||||
provider: str = (
|
||||
"auto" # Provider name (e.g. "anthropic", "openrouter") or "auto" for auto-detection
|
||||
)
|
||||
max_tokens: int = 8192
|
||||
temperature: float = 0.1
|
||||
max_tool_iterations: int = 40
|
||||
@@ -260,8 +263,8 @@ class ProvidersConfig(Base):
|
||||
moonshot: ProviderConfig = Field(default_factory=ProviderConfig)
|
||||
minimax: ProviderConfig = Field(default_factory=ProviderConfig)
|
||||
aihubmix: ProviderConfig = Field(default_factory=ProviderConfig) # AiHubMix API gateway
|
||||
siliconflow: ProviderConfig = Field(default_factory=ProviderConfig) # SiliconFlow (硅基流动) API gateway
|
||||
volcengine: ProviderConfig = Field(default_factory=ProviderConfig) # VolcEngine (火山引擎) API gateway
|
||||
siliconflow: ProviderConfig = Field(default_factory=ProviderConfig) # SiliconFlow (硅基流动)
|
||||
volcengine: ProviderConfig = Field(default_factory=ProviderConfig) # VolcEngine (火山引擎)
|
||||
openai_codex: ProviderConfig = Field(default_factory=ProviderConfig) # OpenAI Codex (OAuth)
|
||||
github_copilot: ProviderConfig = Field(default_factory=ProviderConfig) # Github Copilot (OAuth)
|
||||
|
||||
@@ -291,7 +294,9 @@ class WebSearchConfig(Base):
|
||||
class WebToolsConfig(Base):
|
||||
"""Web tools configuration."""
|
||||
|
||||
proxy: str | None = None # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
|
||||
proxy: str | None = (
|
||||
None # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
|
||||
)
|
||||
search: WebSearchConfig = Field(default_factory=WebSearchConfig)
|
||||
|
||||
|
||||
@@ -305,12 +310,13 @@ class ExecToolConfig(Base):
|
||||
class MCPServerConfig(Base):
|
||||
"""MCP server connection configuration (stdio or HTTP)."""
|
||||
|
||||
type: Literal["stdio", "sse", "streamableHttp"] | None = None # auto-detected if omitted
|
||||
command: str = "" # Stdio: command to run (e.g. "npx")
|
||||
args: list[str] = Field(default_factory=list) # Stdio: command arguments
|
||||
env: dict[str, str] = Field(default_factory=dict) # Stdio: extra env vars
|
||||
url: str = "" # HTTP: streamable HTTP endpoint URL
|
||||
headers: dict[str, str] = Field(default_factory=dict) # HTTP: Custom HTTP Headers
|
||||
tool_timeout: int = 30 # Seconds before a tool call is cancelled
|
||||
url: str = "" # HTTP/SSE: endpoint URL
|
||||
headers: dict[str, str] = Field(default_factory=dict) # HTTP/SSE: custom headers
|
||||
tool_timeout: int = 30 # seconds before a tool call is cancelled
|
||||
|
||||
|
||||
class ToolsConfig(Base):
|
||||
@@ -336,7 +342,9 @@ class Config(BaseSettings):
|
||||
"""Get expanded workspace path."""
|
||||
return Path(self.agents.defaults.workspace).expanduser()
|
||||
|
||||
def _match_provider(self, model: str | None = None) -> tuple["ProviderConfig | None", str | None]:
|
||||
def _match_provider(
|
||||
self, model: str | None = None
|
||||
) -> tuple["ProviderConfig | None", str | None]:
|
||||
"""Match provider config and its registry name. Returns (config, spec_name)."""
|
||||
from nanobot.providers.registry import PROVIDERS
|
||||
|
||||
|
||||
@@ -2,6 +2,7 @@
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import uuid
|
||||
from typing import Any
|
||||
|
||||
import json_repair
|
||||
@@ -15,7 +16,12 @@ class CustomProvider(LLMProvider):
|
||||
def __init__(self, api_key: str = "no-key", api_base: str = "http://localhost:8000/v1", default_model: str = "default"):
|
||||
super().__init__(api_key, api_base)
|
||||
self.default_model = default_model
|
||||
self._client = AsyncOpenAI(api_key=api_key, base_url=api_base)
|
||||
# Keep affinity stable for this provider instance to improve backend cache locality.
|
||||
self._client = AsyncOpenAI(
|
||||
api_key=api_key,
|
||||
base_url=api_base,
|
||||
default_headers={"x-session-affinity": uuid.uuid4().hex},
|
||||
)
|
||||
|
||||
async def chat(self, messages: list[dict[str, Any]], tools: list[dict[str, Any]] | None = None,
|
||||
model: str | None = None, max_tokens: int = 4096, temperature: float = 0.7,
|
||||
|
||||
@@ -8,6 +8,7 @@ from typing import Any
|
||||
import json_repair
|
||||
import litellm
|
||||
from litellm import acompletion
|
||||
from loguru import logger
|
||||
|
||||
from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
|
||||
from nanobot.providers.registry import find_by_model, find_gateway
|
||||
@@ -255,20 +256,37 @@ class LiteLLMProvider(LLMProvider):
|
||||
"""Parse LiteLLM response into our standard format."""
|
||||
choice = response.choices[0]
|
||||
message = choice.message
|
||||
content = message.content
|
||||
finish_reason = choice.finish_reason
|
||||
|
||||
# Some providers (e.g. GitHub Copilot) split content and tool_calls
|
||||
# across multiple choices. Merge them so tool_calls are not lost.
|
||||
raw_tool_calls = []
|
||||
for ch in response.choices:
|
||||
msg = ch.message
|
||||
if hasattr(msg, "tool_calls") and msg.tool_calls:
|
||||
raw_tool_calls.extend(msg.tool_calls)
|
||||
if ch.finish_reason in ("tool_calls", "stop"):
|
||||
finish_reason = ch.finish_reason
|
||||
if not content and msg.content:
|
||||
content = msg.content
|
||||
|
||||
if len(response.choices) > 1:
|
||||
logger.debug("LiteLLM response has {} choices, merged {} tool_calls",
|
||||
len(response.choices), len(raw_tool_calls))
|
||||
|
||||
tool_calls = []
|
||||
if hasattr(message, "tool_calls") and message.tool_calls:
|
||||
for tc in message.tool_calls:
|
||||
# Parse arguments from JSON string if needed
|
||||
args = tc.function.arguments
|
||||
if isinstance(args, str):
|
||||
args = json_repair.loads(args)
|
||||
for tc in raw_tool_calls:
|
||||
# Parse arguments from JSON string if needed
|
||||
args = tc.function.arguments
|
||||
if isinstance(args, str):
|
||||
args = json_repair.loads(args)
|
||||
|
||||
tool_calls.append(ToolCallRequest(
|
||||
id=_short_tool_id(),
|
||||
name=tc.function.name,
|
||||
arguments=args,
|
||||
))
|
||||
tool_calls.append(ToolCallRequest(
|
||||
id=_short_tool_id(),
|
||||
name=tc.function.name,
|
||||
arguments=args,
|
||||
))
|
||||
|
||||
usage = {}
|
||||
if hasattr(response, "usage") and response.usage:
|
||||
@@ -280,11 +298,11 @@ class LiteLLMProvider(LLMProvider):
|
||||
|
||||
reasoning_content = getattr(message, "reasoning_content", None) or None
|
||||
thinking_blocks = getattr(message, "thinking_blocks", None) or None
|
||||
|
||||
|
||||
return LLMResponse(
|
||||
content=message.content,
|
||||
content=content,
|
||||
tool_calls=tool_calls,
|
||||
finish_reason=choice.finish_reason or "stop",
|
||||
finish_reason=finish_reason or "stop",
|
||||
usage=usage,
|
||||
reasoning_content=reasoning_content,
|
||||
thinking_blocks=thinking_blocks,
|
||||
|
||||
@@ -26,33 +26,33 @@ class ProviderSpec:
|
||||
"""
|
||||
|
||||
# identity
|
||||
name: str # config field name, e.g. "dashscope"
|
||||
keywords: tuple[str, ...] # model-name keywords for matching (lowercase)
|
||||
env_key: str # LiteLLM env var, e.g. "DASHSCOPE_API_KEY"
|
||||
display_name: str = "" # shown in `nanobot status`
|
||||
name: str # config field name, e.g. "dashscope"
|
||||
keywords: tuple[str, ...] # model-name keywords for matching (lowercase)
|
||||
env_key: str # LiteLLM env var, e.g. "DASHSCOPE_API_KEY"
|
||||
display_name: str = "" # shown in `nanobot status`
|
||||
|
||||
# model prefixing
|
||||
litellm_prefix: str = "" # "dashscope" → model becomes "dashscope/{model}"
|
||||
skip_prefixes: tuple[str, ...] = () # don't prefix if model already starts with these
|
||||
litellm_prefix: str = "" # "dashscope" → model becomes "dashscope/{model}"
|
||||
skip_prefixes: tuple[str, ...] = () # don't prefix if model already starts with these
|
||||
|
||||
# extra env vars, e.g. (("ZHIPUAI_API_KEY", "{api_key}"),)
|
||||
env_extras: tuple[tuple[str, str], ...] = ()
|
||||
|
||||
# gateway / local detection
|
||||
is_gateway: bool = False # routes any model (OpenRouter, AiHubMix)
|
||||
is_local: bool = False # local deployment (vLLM, Ollama)
|
||||
detect_by_key_prefix: str = "" # match api_key prefix, e.g. "sk-or-"
|
||||
detect_by_base_keyword: str = "" # match substring in api_base URL
|
||||
default_api_base: str = "" # fallback base URL
|
||||
is_gateway: bool = False # routes any model (OpenRouter, AiHubMix)
|
||||
is_local: bool = False # local deployment (vLLM, Ollama)
|
||||
detect_by_key_prefix: str = "" # match api_key prefix, e.g. "sk-or-"
|
||||
detect_by_base_keyword: str = "" # match substring in api_base URL
|
||||
default_api_base: str = "" # fallback base URL
|
||||
|
||||
# gateway behavior
|
||||
strip_model_prefix: bool = False # strip "provider/" before re-prefixing
|
||||
strip_model_prefix: bool = False # strip "provider/" before re-prefixing
|
||||
|
||||
# per-model param overrides, e.g. (("kimi-k2.5", {"temperature": 1.0}),)
|
||||
model_overrides: tuple[tuple[str, dict[str, Any]], ...] = ()
|
||||
|
||||
# OAuth-based providers (e.g., OpenAI Codex) don't use API keys
|
||||
is_oauth: bool = False # if True, uses OAuth flow instead of API key
|
||||
is_oauth: bool = False # if True, uses OAuth flow instead of API key
|
||||
|
||||
# Direct providers bypass LiteLLM entirely (e.g., CustomProvider)
|
||||
is_direct: bool = False
|
||||
@@ -70,7 +70,6 @@ class ProviderSpec:
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
|
||||
# === Custom (direct OpenAI-compatible endpoint, bypasses LiteLLM) ======
|
||||
ProviderSpec(
|
||||
name="custom",
|
||||
@@ -80,17 +79,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
litellm_prefix="",
|
||||
is_direct=True,
|
||||
),
|
||||
|
||||
# === Gateways (detected by api_key / api_base, not model name) =========
|
||||
# Gateways can route any model, so they win in fallback.
|
||||
|
||||
# OpenRouter: global gateway, keys start with "sk-or-"
|
||||
ProviderSpec(
|
||||
name="openrouter",
|
||||
keywords=("openrouter",),
|
||||
env_key="OPENROUTER_API_KEY",
|
||||
display_name="OpenRouter",
|
||||
litellm_prefix="openrouter", # claude-3 → openrouter/claude-3
|
||||
litellm_prefix="openrouter", # claude-3 → openrouter/claude-3
|
||||
skip_prefixes=(),
|
||||
env_extras=(),
|
||||
is_gateway=True,
|
||||
@@ -102,16 +99,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
model_overrides=(),
|
||||
supports_prompt_caching=True,
|
||||
),
|
||||
|
||||
# AiHubMix: global gateway, OpenAI-compatible interface.
|
||||
# strip_model_prefix=True: it doesn't understand "anthropic/claude-3",
|
||||
# so we strip to bare "claude-3" then re-prefix as "openai/claude-3".
|
||||
ProviderSpec(
|
||||
name="aihubmix",
|
||||
keywords=("aihubmix",),
|
||||
env_key="OPENAI_API_KEY", # OpenAI-compatible
|
||||
env_key="OPENAI_API_KEY", # OpenAI-compatible
|
||||
display_name="AiHubMix",
|
||||
litellm_prefix="openai", # → openai/{model}
|
||||
litellm_prefix="openai", # → openai/{model}
|
||||
skip_prefixes=(),
|
||||
env_extras=(),
|
||||
is_gateway=True,
|
||||
@@ -119,10 +115,9 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
detect_by_key_prefix="",
|
||||
detect_by_base_keyword="aihubmix",
|
||||
default_api_base="https://aihubmix.com/v1",
|
||||
strip_model_prefix=True, # anthropic/claude-3 → claude-3 → openai/claude-3
|
||||
strip_model_prefix=True, # anthropic/claude-3 → claude-3 → openai/claude-3
|
||||
model_overrides=(),
|
||||
),
|
||||
|
||||
# SiliconFlow (硅基流动): OpenAI-compatible gateway, model names keep org prefix
|
||||
ProviderSpec(
|
||||
name="siliconflow",
|
||||
@@ -140,7 +135,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(),
|
||||
),
|
||||
|
||||
# VolcEngine (火山引擎): OpenAI-compatible gateway
|
||||
ProviderSpec(
|
||||
name="volcengine",
|
||||
@@ -158,9 +152,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(),
|
||||
),
|
||||
|
||||
# === Standard providers (matched by model-name keywords) ===============
|
||||
|
||||
# Anthropic: LiteLLM recognizes "claude-*" natively, no prefix needed.
|
||||
ProviderSpec(
|
||||
name="anthropic",
|
||||
@@ -179,7 +171,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
model_overrides=(),
|
||||
supports_prompt_caching=True,
|
||||
),
|
||||
|
||||
# OpenAI: LiteLLM recognizes "gpt-*" natively, no prefix needed.
|
||||
ProviderSpec(
|
||||
name="openai",
|
||||
@@ -197,14 +188,13 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(),
|
||||
),
|
||||
|
||||
# OpenAI Codex: uses OAuth, not API key.
|
||||
ProviderSpec(
|
||||
name="openai_codex",
|
||||
keywords=("openai-codex",),
|
||||
env_key="", # OAuth-based, no API key
|
||||
env_key="", # OAuth-based, no API key
|
||||
display_name="OpenAI Codex",
|
||||
litellm_prefix="", # Not routed through LiteLLM
|
||||
litellm_prefix="", # Not routed through LiteLLM
|
||||
skip_prefixes=(),
|
||||
env_extras=(),
|
||||
is_gateway=False,
|
||||
@@ -214,16 +204,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
default_api_base="https://chatgpt.com/backend-api",
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(),
|
||||
is_oauth=True, # OAuth-based authentication
|
||||
is_oauth=True, # OAuth-based authentication
|
||||
),
|
||||
|
||||
# Github Copilot: uses OAuth, not API key.
|
||||
ProviderSpec(
|
||||
name="github_copilot",
|
||||
keywords=("github_copilot", "copilot"),
|
||||
env_key="", # OAuth-based, no API key
|
||||
env_key="", # OAuth-based, no API key
|
||||
display_name="Github Copilot",
|
||||
litellm_prefix="github_copilot", # github_copilot/model → github_copilot/model
|
||||
litellm_prefix="github_copilot", # github_copilot/model → github_copilot/model
|
||||
skip_prefixes=("github_copilot/",),
|
||||
env_extras=(),
|
||||
is_gateway=False,
|
||||
@@ -233,17 +222,16 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
default_api_base="",
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(),
|
||||
is_oauth=True, # OAuth-based authentication
|
||||
is_oauth=True, # OAuth-based authentication
|
||||
),
|
||||
|
||||
# DeepSeek: needs "deepseek/" prefix for LiteLLM routing.
|
||||
ProviderSpec(
|
||||
name="deepseek",
|
||||
keywords=("deepseek",),
|
||||
env_key="DEEPSEEK_API_KEY",
|
||||
display_name="DeepSeek",
|
||||
litellm_prefix="deepseek", # deepseek-chat → deepseek/deepseek-chat
|
||||
skip_prefixes=("deepseek/",), # avoid double-prefix
|
||||
litellm_prefix="deepseek", # deepseek-chat → deepseek/deepseek-chat
|
||||
skip_prefixes=("deepseek/",), # avoid double-prefix
|
||||
env_extras=(),
|
||||
is_gateway=False,
|
||||
is_local=False,
|
||||
@@ -253,15 +241,14 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(),
|
||||
),
|
||||
|
||||
# Gemini: needs "gemini/" prefix for LiteLLM.
|
||||
ProviderSpec(
|
||||
name="gemini",
|
||||
keywords=("gemini",),
|
||||
env_key="GEMINI_API_KEY",
|
||||
display_name="Gemini",
|
||||
litellm_prefix="gemini", # gemini-pro → gemini/gemini-pro
|
||||
skip_prefixes=("gemini/",), # avoid double-prefix
|
||||
litellm_prefix="gemini", # gemini-pro → gemini/gemini-pro
|
||||
skip_prefixes=("gemini/",), # avoid double-prefix
|
||||
env_extras=(),
|
||||
is_gateway=False,
|
||||
is_local=False,
|
||||
@@ -271,7 +258,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(),
|
||||
),
|
||||
|
||||
# Zhipu: LiteLLM uses "zai/" prefix.
|
||||
# Also mirrors key to ZHIPUAI_API_KEY (some LiteLLM paths check that).
|
||||
# skip_prefixes: don't add "zai/" when already routed via gateway.
|
||||
@@ -280,11 +266,9 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
keywords=("zhipu", "glm", "zai"),
|
||||
env_key="ZAI_API_KEY",
|
||||
display_name="Zhipu AI",
|
||||
litellm_prefix="zai", # glm-4 → zai/glm-4
|
||||
litellm_prefix="zai", # glm-4 → zai/glm-4
|
||||
skip_prefixes=("zhipu/", "zai/", "openrouter/", "hosted_vllm/"),
|
||||
env_extras=(
|
||||
("ZHIPUAI_API_KEY", "{api_key}"),
|
||||
),
|
||||
env_extras=(("ZHIPUAI_API_KEY", "{api_key}"),),
|
||||
is_gateway=False,
|
||||
is_local=False,
|
||||
detect_by_key_prefix="",
|
||||
@@ -293,14 +277,13 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(),
|
||||
),
|
||||
|
||||
# DashScope: Qwen models, needs "dashscope/" prefix.
|
||||
ProviderSpec(
|
||||
name="dashscope",
|
||||
keywords=("qwen", "dashscope"),
|
||||
env_key="DASHSCOPE_API_KEY",
|
||||
display_name="DashScope",
|
||||
litellm_prefix="dashscope", # qwen-max → dashscope/qwen-max
|
||||
litellm_prefix="dashscope", # qwen-max → dashscope/qwen-max
|
||||
skip_prefixes=("dashscope/", "openrouter/"),
|
||||
env_extras=(),
|
||||
is_gateway=False,
|
||||
@@ -311,7 +294,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(),
|
||||
),
|
||||
|
||||
# Moonshot: Kimi models, needs "moonshot/" prefix.
|
||||
# LiteLLM requires MOONSHOT_API_BASE env var to find the endpoint.
|
||||
# Kimi K2.5 API enforces temperature >= 1.0.
|
||||
@@ -320,22 +302,17 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
keywords=("moonshot", "kimi"),
|
||||
env_key="MOONSHOT_API_KEY",
|
||||
display_name="Moonshot",
|
||||
litellm_prefix="moonshot", # kimi-k2.5 → moonshot/kimi-k2.5
|
||||
litellm_prefix="moonshot", # kimi-k2.5 → moonshot/kimi-k2.5
|
||||
skip_prefixes=("moonshot/", "openrouter/"),
|
||||
env_extras=(
|
||||
("MOONSHOT_API_BASE", "{api_base}"),
|
||||
),
|
||||
env_extras=(("MOONSHOT_API_BASE", "{api_base}"),),
|
||||
is_gateway=False,
|
||||
is_local=False,
|
||||
detect_by_key_prefix="",
|
||||
detect_by_base_keyword="",
|
||||
default_api_base="https://api.moonshot.ai/v1", # intl; use api.moonshot.cn for China
|
||||
default_api_base="https://api.moonshot.ai/v1", # intl; use api.moonshot.cn for China
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(
|
||||
("kimi-k2.5", {"temperature": 1.0}),
|
||||
),
|
||||
model_overrides=(("kimi-k2.5", {"temperature": 1.0}),),
|
||||
),
|
||||
|
||||
# MiniMax: needs "minimax/" prefix for LiteLLM routing.
|
||||
# Uses OpenAI-compatible API at api.minimax.io/v1.
|
||||
ProviderSpec(
|
||||
@@ -343,7 +320,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
keywords=("minimax",),
|
||||
env_key="MINIMAX_API_KEY",
|
||||
display_name="MiniMax",
|
||||
litellm_prefix="minimax", # MiniMax-M2.1 → minimax/MiniMax-M2.1
|
||||
litellm_prefix="minimax", # MiniMax-M2.1 → minimax/MiniMax-M2.1
|
||||
skip_prefixes=("minimax/", "openrouter/"),
|
||||
env_extras=(),
|
||||
is_gateway=False,
|
||||
@@ -354,9 +331,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(),
|
||||
),
|
||||
|
||||
# === Local deployment (matched by config key, NOT by api_base) =========
|
||||
|
||||
# vLLM / any OpenAI-compatible local server.
|
||||
# Detected when config key is "vllm" (provider_name="vllm").
|
||||
ProviderSpec(
|
||||
@@ -364,20 +339,18 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
keywords=("vllm",),
|
||||
env_key="HOSTED_VLLM_API_KEY",
|
||||
display_name="vLLM/Local",
|
||||
litellm_prefix="hosted_vllm", # Llama-3-8B → hosted_vllm/Llama-3-8B
|
||||
litellm_prefix="hosted_vllm", # Llama-3-8B → hosted_vllm/Llama-3-8B
|
||||
skip_prefixes=(),
|
||||
env_extras=(),
|
||||
is_gateway=False,
|
||||
is_local=True,
|
||||
detect_by_key_prefix="",
|
||||
detect_by_base_keyword="",
|
||||
default_api_base="", # user must provide in config
|
||||
default_api_base="", # user must provide in config
|
||||
strip_model_prefix=False,
|
||||
model_overrides=(),
|
||||
),
|
||||
|
||||
# === Auxiliary (not a primary LLM provider) ============================
|
||||
|
||||
# Groq: mainly used for Whisper voice transcription, also usable for LLM.
|
||||
# Needs "groq/" prefix for LiteLLM routing. Placed last — it rarely wins fallback.
|
||||
ProviderSpec(
|
||||
@@ -385,8 +358,8 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
keywords=("groq",),
|
||||
env_key="GROQ_API_KEY",
|
||||
display_name="Groq",
|
||||
litellm_prefix="groq", # llama3-8b-8192 → groq/llama3-8b-8192
|
||||
skip_prefixes=("groq/",), # avoid double-prefix
|
||||
litellm_prefix="groq", # llama3-8b-8192 → groq/llama3-8b-8192
|
||||
skip_prefixes=("groq/",), # avoid double-prefix
|
||||
env_extras=(),
|
||||
is_gateway=False,
|
||||
is_local=False,
|
||||
@@ -403,6 +376,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
|
||||
# Lookup helpers
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def find_by_model(model: str) -> ProviderSpec | None:
|
||||
"""Match a standard provider by model-name keyword (case-insensitive).
|
||||
Skips gateways/local — those are matched by api_key/api_base instead."""
|
||||
@@ -418,7 +392,9 @@ def find_by_model(model: str) -> ProviderSpec | None:
|
||||
return spec
|
||||
|
||||
for spec in std_specs:
|
||||
if any(kw in model_lower or kw.replace("-", "_") in model_normalized for kw in spec.keywords):
|
||||
if any(
|
||||
kw in model_lower or kw.replace("-", "_") in model_normalized for kw in spec.keywords
|
||||
):
|
||||
return spec
|
||||
return None
|
||||
|
||||
|
||||
@@ -5,6 +5,19 @@ from datetime import datetime
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
def detect_image_mime(data: bytes) -> str | None:
|
||||
"""Detect image MIME type from magic bytes, ignoring file extension."""
|
||||
if data[:8] == b"\x89PNG\r\n\x1a\n":
|
||||
return "image/png"
|
||||
if data[:3] == b"\xff\xd8\xff":
|
||||
return "image/jpeg"
|
||||
if data[:6] in (b"GIF87a", b"GIF89a"):
|
||||
return "image/gif"
|
||||
if data[:4] == b"RIFF" and data[8:12] == b"WEBP":
|
||||
return "image/webp"
|
||||
return None
|
||||
|
||||
|
||||
def ensure_dir(path: Path) -> Path:
|
||||
"""Ensure directory exists, return it."""
|
||||
path.mkdir(parents=True, exist_ok=True)
|
||||
@@ -34,6 +47,38 @@ def safe_filename(name: str) -> str:
|
||||
return _UNSAFE_CHARS.sub("_", name).strip()
|
||||
|
||||
|
||||
def split_message(content: str, max_len: int = 2000) -> list[str]:
|
||||
"""
|
||||
Split content into chunks within max_len, preferring line breaks.
|
||||
|
||||
Args:
|
||||
content: The text content to split.
|
||||
max_len: Maximum length per chunk (default 2000 for Discord compatibility).
|
||||
|
||||
Returns:
|
||||
List of message chunks, each within max_len.
|
||||
"""
|
||||
if not content:
|
||||
return []
|
||||
if len(content) <= max_len:
|
||||
return [content]
|
||||
chunks: list[str] = []
|
||||
while content:
|
||||
if len(content) <= max_len:
|
||||
chunks.append(content)
|
||||
break
|
||||
cut = content[:max_len]
|
||||
# Try to break at newline first, then space, then hard break
|
||||
pos = cut.rfind('\n')
|
||||
if pos <= 0:
|
||||
pos = cut.rfind(' ')
|
||||
if pos <= 0:
|
||||
pos = max_len
|
||||
chunks.append(content[:pos])
|
||||
content = content[pos:].lstrip()
|
||||
return chunks
|
||||
|
||||
|
||||
def sync_workspace_templates(workspace: Path, silent: bool = False) -> list[str]:
|
||||
"""Sync bundled templates to workspace. Only creates missing files."""
|
||||
from importlib.resources import files as pkg_files
|
||||
|
||||
@@ -30,7 +30,7 @@ dependencies = [
|
||||
"rich>=14.0.0,<15.0.0",
|
||||
"croniter>=6.0.0,<7.0.0",
|
||||
"dingtalk-stream>=0.24.0,<1.0.0",
|
||||
"python-telegram-bot[socks]>=22.0,<23.0",
|
||||
"python-telegram-bot[socks]>=22.6,<23.0",
|
||||
"lark-oapi>=1.5.0,<2.0.0",
|
||||
"socksio>=1.0.0,<2.0.0",
|
||||
"python-socketio>=5.16.0,<6.0.0",
|
||||
|
||||
104
tests/test_feishu_table_split.py
Normal file
104
tests/test_feishu_table_split.py
Normal file
@@ -0,0 +1,104 @@
|
||||
"""Tests for FeishuChannel._split_elements_by_table_limit.
|
||||
|
||||
Feishu cards reject messages that contain more than one table element
|
||||
(API error 11310: card table number over limit). The helper splits a flat
|
||||
list of card elements into groups so that each group contains at most one
|
||||
table, allowing nanobot to send multiple cards instead of failing.
|
||||
"""
|
||||
|
||||
from nanobot.channels.feishu import FeishuChannel
|
||||
|
||||
|
||||
def _md(text: str) -> dict:
|
||||
return {"tag": "markdown", "content": text}
|
||||
|
||||
|
||||
def _table() -> dict:
|
||||
return {
|
||||
"tag": "table",
|
||||
"columns": [{"tag": "column", "name": "c0", "display_name": "A", "width": "auto"}],
|
||||
"rows": [{"c0": "v"}],
|
||||
"page_size": 2,
|
||||
}
|
||||
|
||||
|
||||
split = FeishuChannel._split_elements_by_table_limit
|
||||
|
||||
|
||||
def test_empty_list_returns_single_empty_group() -> None:
|
||||
assert split([]) == [[]]
|
||||
|
||||
|
||||
def test_no_tables_returns_single_group() -> None:
|
||||
els = [_md("hello"), _md("world")]
|
||||
result = split(els)
|
||||
assert result == [els]
|
||||
|
||||
|
||||
def test_single_table_stays_in_one_group() -> None:
|
||||
els = [_md("intro"), _table(), _md("outro")]
|
||||
result = split(els)
|
||||
assert len(result) == 1
|
||||
assert result[0] == els
|
||||
|
||||
|
||||
def test_two_tables_split_into_two_groups() -> None:
|
||||
# Use different row values so the two tables are not equal
|
||||
t1 = {
|
||||
"tag": "table",
|
||||
"columns": [{"tag": "column", "name": "c0", "display_name": "A", "width": "auto"}],
|
||||
"rows": [{"c0": "table-one"}],
|
||||
"page_size": 2,
|
||||
}
|
||||
t2 = {
|
||||
"tag": "table",
|
||||
"columns": [{"tag": "column", "name": "c0", "display_name": "B", "width": "auto"}],
|
||||
"rows": [{"c0": "table-two"}],
|
||||
"page_size": 2,
|
||||
}
|
||||
els = [_md("before"), t1, _md("between"), t2, _md("after")]
|
||||
result = split(els)
|
||||
assert len(result) == 2
|
||||
# First group: text before table-1 + table-1
|
||||
assert t1 in result[0]
|
||||
assert t2 not in result[0]
|
||||
# Second group: text between tables + table-2 + text after
|
||||
assert t2 in result[1]
|
||||
assert t1 not in result[1]
|
||||
|
||||
|
||||
def test_three_tables_split_into_three_groups() -> None:
|
||||
tables = [
|
||||
{"tag": "table", "columns": [], "rows": [{"c0": f"t{i}"}], "page_size": 1}
|
||||
for i in range(3)
|
||||
]
|
||||
els = tables[:]
|
||||
result = split(els)
|
||||
assert len(result) == 3
|
||||
for i, group in enumerate(result):
|
||||
assert tables[i] in group
|
||||
|
||||
|
||||
def test_leading_markdown_stays_with_first_table() -> None:
|
||||
intro = _md("intro")
|
||||
t = _table()
|
||||
result = split([intro, t])
|
||||
assert len(result) == 1
|
||||
assert result[0] == [intro, t]
|
||||
|
||||
|
||||
def test_trailing_markdown_after_second_table() -> None:
|
||||
t1, t2 = _table(), _table()
|
||||
tail = _md("end")
|
||||
result = split([t1, t2, tail])
|
||||
assert len(result) == 2
|
||||
assert result[1] == [t2, tail]
|
||||
|
||||
|
||||
def test_non_table_elements_before_first_table_kept_in_first_group() -> None:
|
||||
head = _md("head")
|
||||
t1, t2 = _table(), _table()
|
||||
result = split([head, t1, t2])
|
||||
# head + t1 in group 0; t2 in group 1
|
||||
assert result[0] == [head, t1]
|
||||
assert result[1] == [t2]
|
||||
@@ -145,3 +145,78 @@ class TestMemoryConsolidationTypeHandling:
|
||||
|
||||
assert result is True
|
||||
provider.chat.assert_not_called()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_list_arguments_extracts_first_dict(self, tmp_path: Path) -> None:
|
||||
"""Some providers return arguments as a list - extract first element if it's a dict."""
|
||||
store = MemoryStore(tmp_path)
|
||||
provider = AsyncMock()
|
||||
|
||||
# Simulate arguments being a list containing a dict
|
||||
response = LLMResponse(
|
||||
content=None,
|
||||
tool_calls=[
|
||||
ToolCallRequest(
|
||||
id="call_1",
|
||||
name="save_memory",
|
||||
arguments=[{
|
||||
"history_entry": "[2026-01-01] User discussed testing.",
|
||||
"memory_update": "# Memory\nUser likes testing.",
|
||||
}],
|
||||
)
|
||||
],
|
||||
)
|
||||
provider.chat = AsyncMock(return_value=response)
|
||||
session = _make_session(message_count=60)
|
||||
|
||||
result = await store.consolidate(session, provider, "test-model", memory_window=50)
|
||||
|
||||
assert result is True
|
||||
assert "User discussed testing." in store.history_file.read_text()
|
||||
assert "User likes testing." in store.memory_file.read_text()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_list_arguments_empty_list_returns_false(self, tmp_path: Path) -> None:
|
||||
"""Empty list arguments should return False."""
|
||||
store = MemoryStore(tmp_path)
|
||||
provider = AsyncMock()
|
||||
|
||||
response = LLMResponse(
|
||||
content=None,
|
||||
tool_calls=[
|
||||
ToolCallRequest(
|
||||
id="call_1",
|
||||
name="save_memory",
|
||||
arguments=[],
|
||||
)
|
||||
],
|
||||
)
|
||||
provider.chat = AsyncMock(return_value=response)
|
||||
session = _make_session(message_count=60)
|
||||
|
||||
result = await store.consolidate(session, provider, "test-model", memory_window=50)
|
||||
|
||||
assert result is False
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_list_arguments_non_dict_content_returns_false(self, tmp_path: Path) -> None:
|
||||
"""List with non-dict content should return False."""
|
||||
store = MemoryStore(tmp_path)
|
||||
provider = AsyncMock()
|
||||
|
||||
response = LLMResponse(
|
||||
content=None,
|
||||
tool_calls=[
|
||||
ToolCallRequest(
|
||||
id="call_1",
|
||||
name="save_memory",
|
||||
arguments=["string", "content"],
|
||||
)
|
||||
],
|
||||
)
|
||||
provider.chat = AsyncMock(return_value=response)
|
||||
session = _make_session(message_count=60)
|
||||
|
||||
result = await store.consolidate(session, provider, "test-model", memory_window=50)
|
||||
|
||||
assert result is False
|
||||
|
||||
Reference in New Issue
Block a user